Amel Ben Slimane Rahmouni

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This paper presents a robust algorithm for glottal closure instants (GCIs) detection of speech signals. The algorithm uses a multi-scale analysis based on a dyadic wavelet filterbank. Significant minima and maxima of the filtered signals are localized at each scale using adap-tive mathematical morphology transformation of erosion. With reference to the GCIs(More)
identification suffer from the problem of co-channel speech. This paper deals with a multi-resolution dyadic wavelet transform method for usable segments of co-channel speech detection that could be processed by a speaker identification system. Evaluation of this method is performed on TIMIT database referring to the Target to Interferer Ratio measure.(More)
Usable speech criteria are proposed to extract minimally corrupted speech for speaker identification (SID) in co-channel speech. In co-channel speech, either speaker can randomly appear as the stronger speaker or the weaker one at a time. Hence, the extracted usable segments are separated in time and need to be organized into speaker streams for SID. In(More)
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